{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,26]],"date-time":"2025-11-26T16:28:53Z","timestamp":1764174533109,"version":"build-2065373602"},"reference-count":41,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2018,6,25]],"date-time":"2018-06-25T00:00:00Z","timestamp":1529884800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["No. 41571360, No. 41371335, No. 41671356, and No. 41531068"],"award-info":[{"award-number":["No. 41571360, No. 41371335, No. 41671356, and No. 41531068"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002946","name":"Deutsches Zentrum f\u00fcr Luft- und Raumfahrt","doi-asserted-by":"publisher","award":["MTH2350 and LAN2235"],"award-info":[{"award-number":["MTH2350 and LAN2235"]}],"id":[{"id":"10.13039\/501100002946","id-type":"DOI","asserted-by":"publisher"}]},{"name":"he Natural Science Foundation of Hunan Province, China","award":["No. 2016JJ2141"],"award-info":[{"award-number":["No. 2016JJ2141"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Synthetic aperture radar tomography (TomoSAR) is a useful tool for retrieving the three-dimensional structure of buildings in urban areas, especially for datasets with a high spatial resolution. However, among the previous TomoSAR estimators, some cannot retrieve the 3-D structure of objects with a high elevation resolution, some cannot maintain the spatial resolution, and some require the selection of a hyperparameter. To overcome these limitations, this paper proposes a new nonparametric iterative adaptive approach with a model selection tool based on the Bayesian information criterion (IAA-BIC) for the application of TomoSAR in urban areas. IAA-BIC employs weighted least squares to acquire a high elevation resolution and works well for both distributed and coherent scatterers, even with single-look. Concurrently, IAA-BIC does not require the user to make any difficult selection regarding a hyperparameter. The proposed IAA-BIC estimator was tested in simulated experiments, and the results confirmed the advantages of the IAA-BIC estimator. Moreover, the three-dimensional structure of the Hubei Science and Technology Venture building in Wuhan, China, was retrieved through the IAA-BIC method with nine very high spatial resolution TerraSAR-X images. The height estimation accuracy for this building was about 1% and 4% relative to its real height for single-look and multi-look, respectively. In addition, a comparison between the IAA-BIC estimator and some of the typical existing TomoSAR estimators (Capon, MUSIC, and compressed sensing (CS)) was also carried out. The results indicate that the IAA-BIC estimator obtains a better resolution for coherent sources than Capon and MUSIC; notably, the IAA-BIC estimator obtains a similar performance to CS, but in less computation time.<\/jats:p>","DOI":"10.3390\/rs10071004","type":"journal-article","created":{"date-parts":[[2018,6,25]],"date-time":"2018-06-25T11:03:25Z","timestamp":1529924605000},"page":"1004","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Three-Dimensional Structure Inversion of Buildings with Nonparametric Iterative Adaptive Approach Using SAR Tomography"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9240-6347","authenticated-orcid":false,"given":"Xing","family":"Peng","sequence":"first","affiliation":[{"name":"School of Geosciences and Info-Physics, Central South University, Changsha 410083, China"},{"name":"Key Lab of Digital Earth Sciences, Institute of Remote Sensing &amp; Digital Earth, Chinese Academy of Sciences, Beijing 100094, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4461-068X","authenticated-orcid":false,"given":"Changcheng","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Geosciences and Info-Physics, Central South University, Changsha 410083, China"},{"name":"Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring, Ministry of Education, Central South University, Changsha 410083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xinwu","family":"Li","sequence":"additional","affiliation":[{"name":"Key Lab of Digital Earth Sciences, Institute of Remote Sensing &amp; Digital Earth, Chinese Academy of Sciences, Beijing 100094, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1277-564X","authenticated-orcid":false,"given":"Yanan","family":"Du","sequence":"additional","affiliation":[{"name":"School of Geographical Sciences, Guangzhou University, Guangzhou 510006, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haiqiang","family":"Fu","sequence":"additional","affiliation":[{"name":"School of Geosciences and Info-Physics, Central South University, Changsha 410083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9816-8562","authenticated-orcid":false,"given":"Zefa","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Geosciences and Info-Physics, Central South University, Changsha 410083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4293-3354","authenticated-orcid":false,"given":"Qinghua","family":"Xie","sequence":"additional","affiliation":[{"name":"Faculty of Information Engineering, China University of Geoscience (Wuhan), Wuhan 430074, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2018,6,25]]},"reference":[{"unstructured":"Roth, A. 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